What is research-workflow?

A research workflow for answering questions with web, documentation, code, academic, and social-media sources.

Use it for fact checks, comparisons, explanations, documentation lookups, and research that needs several sources.

It helps choose suitable research tools and combine their results instead of searching each source manually.

research-workflow — Skill for Claude Code and Codex by yoloshii

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add yoloshii/gigaxity-deep-research --skill research-workflow

Clone the repo

git clone --depth 1 https://github.com/yoloshii/gigaxity-deep-research

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/yoloshii/gigaxity-deep-research/research-workflow/github.svg)](https://agentmods.dev/skills/yoloshii/gigaxity-deep-research/research-workflow)

Your own site

<a href="https://agentmods.dev/skills/yoloshii/gigaxity-deep-research/research-workflow"><img src="https://agentmods.dev/badge/skills/yoloshii/gigaxity-deep-research/research-workflow/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/yoloshii/gigaxity-deep-research/research-workflow"><img src="https://agentmods.dev/badge/skills/yoloshii/gigaxity-deep-research/research-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 22,563 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 6 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

high Anti-Refusal · line 1275
Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.

Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
medium Data Exfiltration · line 1645
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
medium Data Exfiltration · line 1651
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
medium Data Exfiltration · line 1655
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
medium Data Exfiltration · line 1658
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
low Supply Chain · line 1642
Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.

Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00102	$0.22563
Opus 5	$0.00051	$0.11281
Sonnet 5	$0.00020	$0.04513
Haiku 4.5	$0.00010	$0.02256

Measured 11d ago against content hash 5315809b8374, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

research-workflow scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s -o /dev/null -w "%{http_code}" -L "https://github.com/<owner>/<repo>"

skills/research-workflow/SKILL.md · 1,711 lines

How it starts

The opening of the file, as written. The whole thing — 1,711 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Workflow Skill

Overview

This skill orchestrates research queries using the optimal workflow based on query type. It integrates:

Triple Stack: Context7 (docs) + Exa (code/web) + Jina (web/academic/parallel)
gigaxity-deep-research: synthesis engine over any OpenAI-compatible chat-completions endpoint (self-hosted vLLM/SGLang/llama.cpp on the local-inference branch, OpenRouter on main)
exa-answer: speed-critical 1–2 s factual lookups
brightdata_fallback: blocked-URL recovery (CAPTCHA / paywall / Cloudflare)
gptr-mcp: social-first research over Reddit, X/Twitter, YouTube — wraps GPT Researcher

Tool Schema Loading (MANDATORY)

MCP tool schemas are deferred. Bare mcp__X__Y(...) calls fail with InputValidationError because the schema isn't loaded. Load schemas first via ToolSearch:

ToolSearch(query='select:mcp__context7__resolve-library-id,mcp__context7__query-docs')   # docs (two-step)
ToolSearch(query='select:mcp__exa__web_search_exa,mcp__jina__read_url')      # multiple
ToolSearch(query='+exa-answer')                                              # keyword (rank by relevance)

After ToolSearch returns the <function>... block for a tool, that tool is callable for the rest of the session — no need to re-load.

Why this matters: if you skip ToolSearch and the bare call fails, the path of least resistance is to fall through to WebFetch / WebSearch — neither is in the Triple Stack. Using them is the strongest signal that schema loading was skipped.

❌ mcp__context7__query-docs(libraryId="...", query="...")      # fails — schema not loaded
✅ ToolSearch(query='select:mcp__context7__resolve-library-id,mcp__context7__query-docs')
   → then mcp__context7__resolve-library-id(...) → mcp__context7__query-docs(...)   # works

❌ Tool fails silently → fall back to WebFetch
✅ Tool fails → check whether schema was loaded → ToolSearch + retry

Subagents inherit the same deferred-loading discipline — when spawning a research subagent via the Task tool, the subagent prompt MUST include ToolSearch(query='select:...') ahead of every mcp__X__Y reference, otherwise the subagent will fall through to WebFetch the same way.

Read the full file on GitHub · 1,711 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

11d ago First seen · 1,711 lines · 102 tokens per session scan A 5315809b8374

Subscribe to this mod's changes

research-workflow is a skill published in the GitHub repository yoloshii/gigaxity-deep-research (59 stars, last pushed yesterday), licensed MIT. It adds 102 tokens to every session and 22,563 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Claude Code Research agentic-ai agentic-search ai-agents ai-research-agent ai-research-tool

worker-integration

Worker-Agent integration for intelligent task dispatch and performance tracking.

ruvnet/ruflo · 14 tokens

foundry-config-setup

Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.

microsoft/agent-framework · 65 tokens

research-workflow